Detection Algorithm of BPSK Signal of Parameter-Adjusted Bistable Stochastic Resonance Model Based on Scale Change

摘要: Given that signal is weakened to a certain extent in the process of noise suppression using mainstream method, and new introduced by processing system, causing decrease detection performance, improve performance BPSK under condition strong no prior information, algorithm bistable stochastic resonance model based on scale change proposed this study. Using classical (BSR) only low-amplitude low-frequency periodic can be processed. Scale first made BSR study, verifying applied high-frequency high sampling frequency condition, nonlinear threshold system designed following Neyman-Pearson criterion deduce quantitatively show error rate detector. Besides, complete flow for was built taking it as feedback quantity adjust parameters adaptively. feasibility applicability study were verified through simulation experiment, which lays theoretical basis weak low signal-to-noise ratio (SNR).